In modern wireless cellular systems, for example in High Speed Packet Access or HSPA, fast Link Adaptation (LA) is used in the downlink (DL) to control the data transmission rate between the transmitter and the receiver. For example, the receiver is a User Equipment or “UE” in the parlance used by the Third Generation Partnership Project (3GPP), and the transmitter is a network base station (BS), such as a “NodeB” in Wideband CDMA (WCDMA) networks or “eNodeB” in Long Term Evolution (LTE) networks.
The UE estimates the received signal quality of its serving cell signal during the current Transmit Time Interval (TTI) and reports the signal quality to the serving BS via a Channel Quality Indicator (CQI) report. For example, the UE estimates the signal-to-noise-plus-interference ratio (SINR) of the received serving cell signal, maps the SINR to a CQI value, and reports the CQI value to the serving BS.
The serving BS performs LA with respect to the UE based on the CQI values reported by the UE. LA examples include the BS using the CQI reports from the UE to schedule proper modulation and transport formats for transmitting to the UE in a future TTI. Here, “proper” denotes a modulation and coding scheme (MCS) that results in the UE decoding received transport blocks with a desired probability of success, e.g., with a BLock Error Rate (BLER) of ten percent or less. Thus, the BS adjusts the MCS used for transmitting to the UE in a future TTI based on the CQI reported by the UE for the current or past TTIs. Of course, this approach to LA assumes that reception conditions at the UE in the future TTI will be the same or similar to the reception conditions on which the CQI report is based.
The assumption holds for scenarios where the received signal quality at the UE is relatively constant relative to LA delay—i.e., the scheduling delay between the time the UE reports CQI and the data transmission to the UE that is based on the reported CQI. In HSPA, for example, such delays are typically around 3 TTIs or 6 milliseconds. That amount of time is of little consequence when reception conditions generally do not change rapidly, such as is the case for linear receivers when they are used at low-to-medium vehicular speeds in a relatively stable interference environment. The interference environment within a cellular communication network is stable, for example, when loading (activity) is constant within the cells neighboring a given serving cell. Traditional CQI reporting works well for stable interference environments, leading to near-optimal scheduling of UEs in such environments.
Conversely, in other scenarios, the demodulated signal quality experienced by a given UE varies significantly from one TTI to another. Consider advanced UE receiver architectures that perform other-cell interference cancellation (IC). Receivers of that type perform regeneration of interfering signals and use the regenerated signals to remove corresponding interference from the received signal and thereby improve the effective, post-IC SINR of the received signal.
Some IC receivers apply “soft” IC that can remove a fraction of the interfering signal energy even when the signal cannot be successfully decoded. The removable fraction of interference or “cancellation efficiency” (CE) depends on the reception quality of the interfering signal at the victim UE and on its MCS. Unfortunately, in real-world network deployments, the users served in any given cell may have widely disparate channel qualities with corresponding variations in the MCSs used to serve those users. Thus, the CE achievable via IC processing at an interfered, victim UE in a neighboring cell varies unpredictably with respect to the interfering transmissions to neighbor-cell users. Consequently, practical CQI reporting and corresponding LA approaches do not attempt to account for the instantaneous IC gains at UEs that have IC receivers. Instead, it is known to account for the effects of IC at UEs by applying an offset to measured or reported SINR (or CQI).
For example, certain BS scheduler implementations include a CQI offset “outer loop” where a UE-specific SINR offset is applied to the SINR info extracted from the received CQI reports from that UE. The offset accounts for the fact that the CQI values reported by a UE may include a systematic bias error and do not necessarily lead to the target BLER. The offset is designed to shift the actual SINR-to-MCS mapping in scheduling so as to make the actual first transmission BLER equal to the target BLER value. In a similar approach, the CQI outer loop is not implemented at the BS and instead is emulated on the UE side, based on the UE observing first-transmission BLER and adjusting reported signal quality by an offset that drives the long-term BLER to the desired value.
The use of such SINR offsets addresses the problem of varying CE at an IC UE in the sense that the offset is fixed or slowly changing and corresponds to an average efficiency or some other relatively conservative estimate of CE at the UE. However, while this conservative approach generally avoids the selection of MCS values that are too aggressive with respect to the actual CE realizable at the UE in the instantaneous sense, it is recognized herein that this approach fails to exploit instances of higher CE at the UE. That failure results in lower than achievable throughput to the UE.